Interactions between climate change, urban infrastructure and mobility are driving dengue emergence in Vietnam.

Dengue is expanding globally, but how dengue emergence is shaped locally by interactions between climatic and socio-environmental factors is not well understood. Here, we investigate the drivers of dengue incidence and emergence in Vietnam, through analysing 23 years of district-level case data spanning a period of significant socioeconomic change (1998-2020). We show that urban infrastructure factors (sanitation, water supply, long-term urban growth) predict local spatial patterns of dengue incidence, while human mobility is a more influential driver in subtropical northern regions than the endemic south. Temperature is the dominant factor shaping dengue's distribution and dynamics, and using long-term reanalysis temperature data we show that warming since 1950 has expanded transmission risk throughout Vietnam, and most strongly in current dengue emergence hotspots (e.g., southern central regions, Ha Noi). In contrast, effects of hydrometeorology are complex, multi-scalar and dependent on local context: risk increases under either short-term precipitation excess or long-term drought, but improvements in water supply mitigate drought-associated risks except under extreme conditions. Our findings challenge the assumption that dengue is an urban disease, instead suggesting that incidence peaks in transitional landscapes with intermediate infrastructure provision, and provide evidence that interactions between recent climate change and mobility are contributing to dengue's expansion throughout Vietnam.

Probabilistic seasonal dengue forecasting in Vietnam: A modelling study using superensembles.

BACKGROUND: With enough advanced notice, dengue outbreaks can be mitigated. As a climate-sensitive disease, environmental conditions and past patterns of dengue can be used to make predictions about future outbreak risk. These predictions improve public health planning and decision-making to ultimately reduce the burden of disease. Past approaches to dengue forecasting have used seasonal climate forecasts, but the predictive ability of a system using different lead times in a year-round prediction system has been seldom explored. Moreover, the transition from theoretical to operational systems integrated with disease control activities is rare. METHODS AND FINDINGS: We introduce an operational seasonal dengue forecasting system for Vietnam where Earth observations, seasonal climate forecasts, and lagged dengue cases are used to drive a superensemble of probabilistic dengue models to predict dengue risk up to 6 months ahead. Bayesian spatiotemporal models were fit to 19 years (2002-2020) of dengue data at the province level across Vietnam. A superensemble of these models then makes probabilistic predictions of dengue incidence at various future time points aligned with key Vietnamese decision and planning deadlines. We demonstrate that the superensemble generates more accurate predictions of dengue incidence than the individual models it incorporates across a suite of time horizons and transmission settings. Using historical data, the superensemble made slightly more accurate predictions (continuous rank probability score [CRPS] = 66.8, 95% CI 60.6-148.0) than a baseline model which forecasts the same incidence rate every month (CRPS = 79.4, 95% CI 78.5-80.5) at lead times of 1 to 3 months, albeit with larger uncertainty. The outbreak detection capability of the superensemble was considerably larger (69%) than that of the baseline model (54.5%). Predictions were most accurate in southern Vietnam, an area that experiences semi-regular seasonal dengue transmission. The system also demonstrated added value across multiple areas compared to previous practice of not using a forecast. We use the system to make a prospective prediction for dengue incidence in Vietnam for the period May to October 2020. Prospective predictions made with the superensemble were slightly more accurate (CRPS = 110, 95% CI 102-575) than those made with the baseline model (CRPS = 125, 95% CI 120-168) but had larger uncertainty. Finally, we propose a framework for the evaluation of probabilistic predictions. Despite the demonstrated value of our forecasting system, the approach is limited by the consistency of the dengue case data, as well as the lack of publicly available, continuous, and long-term data sets on mosquito control efforts and serotype-specific case data. CONCLUSIONS: This study shows that by combining detailed Earth observation data, seasonal climate forecasts, and state-of-the-art models, dengue outbreaks can be predicted across a broad range of settings, with enough lead time to meaningfully inform dengue control. While our system omits some important variables not currently available at a subnational scale, the majority of past outbreaks could be predicted up to 3 months ahead. Over the next 2 years, the system will be prospectively evaluated and, if successful, potentially extended to other areas and other climate-sensitive disease systems.

Job Displacement and First Birth Over the Business Cycle.

In this article, we investigate the impact of job displacement on women's first-birth rates as well as the variation in this effect over the business cycle. We use mass layoffs to estimate the causal effects of involuntary job loss on fertility in the short and medium term, up to five years after displacement. Our analysis is based on rich administrative data from Germany, with an observation period spanning more than 20 years. We apply inverse probability weighting (IPW) to flexibly control for the observed differences between women who were and were not displaced. To account for the differences in the composition of the women who were displaced in a downturn and the women who were displaced in an upswing, we use a double weighting estimator. Results show that the extent to which job displacement has adverse effects on fertility depends on the business cycle. The first-birth rates were much lower for women who were displaced in an economic downturn than for those who lost a job in an economic upturn. This result cannot be explained by changes in the observed characteristics of the displaced women over the business cycle.

Mesh graft infection following abdominal hernia repair: risk factor evaluation and strategies of mesh graft preservation. A retrospective analysis of 476 operations.

BACKGROUND: Mesh graft infection after prosthetic hernia repair is a challenging complication usually treated by mesh removal. The aim of this study was to identify risk factors associated with mesh infection and to assess the efficacy of conservative wound therapy in preserving an infected mesh. METHODS: We performed a retrospective analysis of 476 consecutive patients with incisional hernia who received mesh graft repair between February 1, 2000 and February 28, 2005 at our institution using chart review and clinical investigation. RESULTS: Thirty-one of 476 (6.5%) patients developed a deep surgical site infection involving the implanted mesh graft. Upon multivariate analysis, operation time was the only significant risk factor associated with mesh infection (p = 0.0038). Seventeen (55%) of 31 infected mesh grafts were preserved by conservative means. There was a significant association between the type of mesh graft used and the probability of mesh preservation in case of infection: While conservative therapy led to preservation of 100% of infected polyglactin/polypropylene meshes, only 20% of infected polypropylene and 23% of infected PTFE/polypropylene meshes could be salvaged using conservative means (p < 0.0001). In none of the patients with preserved mesh graft was hernia recurrence at the former site of infection observed. CONCLUSIONS: Operation time is the only significant risk factor associated with mesh graft infection following incisional hernia repair. Conservative treatment should be applied in case of infection of absorbable mesh grafts such as polypropylene/polyglactin, while nonabsorbable meshes such as PTFE/polypropylene or pure polypropylene are much less amenable to conservative treatment, usually requiring early surgical removal.